We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
—One of the major challenges in multi-view imaging is the definition of a representation that reveals the intrinsic geometry of the visual information. Sparse image representati...
This paper introduces a new concept, a decision tree (or list) over tree patterns, which is a natural extension of a decision tree (or decision list), for dealing with tree struct...
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
This paper describes the application of machine learning methods to determine parameters for DeLite, a readability checking tool. DeLite pinpoints text segments that are difficul...